@article { author = {A. Al-Obaidi, Saadi and N. Al-Tikriti, Munther and Gh. Al-Ghizi, Ammar}, title = {Tuning of Composite Fuzzy Logic Guidance Law Using Genetic Algorithms}, journal = {Engineering and Technology Journal}, volume = {30}, number = {13}, pages = {2341-2356}, year = {2012}, publisher = {University of Technology-Iraq}, issn = {1681-6900}, eissn = {2412-0758}, doi = {10.30684/etj.30.13.13}, abstract = {The application of Fuzzy Logic (FL) for the development of guidance laws for homing missile is presented. Fuzzy logic has been used to develop a Composite Fuzzy Guidance (CFG) law. The objective of this proposed guidance law is to combine desirable features of PN and APN homing guidance laws to enhance the interception of targets performing uncertain maneuvers without reaching the missile to saturation limit. During this work, it became apparent that the fuzzy controller of the CFG law can be further tuned to enhance its performance. Genetic Algorithms (GAs) which are inspired by natural genetics are one of the algorithms that can be used to tune the parameters of fuzzy controllers due to the promising results that they introduced in the field of optimization. This paper introduces the integration of GAs and FL with a main emphasis on tuning the membership function parameters of fuzzy logic controller of the proposed CFG law using Genetic Algorithms (GAs) with the view to improve its performance. The simulation has been performed using Borland C++ programming language (version 5.02) along with the Matlab programming package (version 7.0) that has been used for plotting the results of simulations.}, keywords = {Guidance Law,Fuzzy Logic Control,Genetic algorithms}, url = {https://etj.uotechnology.edu.iq/article_60867.html}, eprint = {https://etj.uotechnology.edu.iq/article_60867_566c68de0e8cf02618dce9675ac3cd05.pdf} }